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Frontal Object Perception Using Radar and Mono-Vision

Abstract : In this paper, we detail a complete software architecture of a key task that an intelligent vehicle has to deal with: frontal object perception. This task is solved by processing raw data of a radar and a mono-camera to detect and track moving objects. Data sets obtained from highways, country roads and urban areas were used to test the proposed method. Several experiments were conducted to show that the proposed method obtains a better environment representation, i.e., reduces the false alarms and missed detections from individual sensor evidence.
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https://hal.archives-ouvertes.fr/hal-00741151
Contributor : Olivier Aycard <>
Submitted on : Thursday, October 11, 2012 - 7:04:31 PM
Last modification on : Monday, April 20, 2020 - 11:24:01 AM

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Omar Chavez-Garcia, Julien Burlet, Trung-Dung Vu, Olivier Aycard. Frontal Object Perception Using Radar and Mono-Vision. 2012 Intelligent Vehicles Symposium, Jun 2012, Alcalá de Henares, Spain. pp.159-164, ⟨10.1109/IVS.2012.6232307⟩. ⟨hal-00741151⟩

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